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一种利用 CK7、TTF1、β-连环蛋白、CDX2 和 SSTR2A 的算法方法可有助于鉴别胃肠道和肺神经内分泌癌。

An algorithmic approach utilizing CK7, TTF1, beta-catenin, CDX2, and SSTR2A can help differentiate between gastrointestinal and pulmonary neuroendocrine carcinomas.

机构信息

Department of Pathology and Laboratory Medicine, Tufts Medical Center, Boston, MA, USA.

Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA.

出版信息

Virchows Arch. 2021 Sep;479(3):481-491. doi: 10.1007/s00428-021-03085-7. Epub 2021 Mar 17.

Abstract

Primary gastrointestinal neuroendocrine carcinoma (GI-NEC) cannot be distinguished morphologically from pulmonary neuroendocrine carcinoma (P-NEC). This can present a significant diagnostic challenge in cases where site of origin cannot be readily determined. To identify immunohistochemical (IHC) markers that can be used to reliably distinguish between GI-NECs and P-NECs, we constructed 3-mm tissue microarrays, one containing 13 GI-NECs and one containing 20 P-NECs. IHC was performed on both microarrays using 21 stains: AE1/AE3, CK7, CK20, synaptophysin, chromogranin, CD56, INSM1, SSTR2A, CDX2, SATB2, TTF1, Napsin A, PR, GATA3, PAX8, ISL1, beta-catenin, AFP, SMAD4, Rb, and p53. For GI-NEC, the most strongly expressed marker was synaptophysin (mean H-score 248), while AE1/AE3 was the most strongly expressed in P-NEC (mean H-score 230), which was stronger than in GI-NEC (p = 0.011). Other markers that were stronger overall in P-NEC than in GI-NEC included CK7 (p < 0.0001) and TTF1 (p < 0.0001). Markers that were stronger overall in GI-NEC than in P-NEC included SSTR2A (p = 0.0021), SATB2 (p = 0.018), CDX2 (p = 0.019), and beta-catenin (nuclear; p = 0.029). SMAD4, Rb, and p53 showed similar rates of abnormal protein expression. Based on these results, a stepwise algorithmic approach utilizing CK7, TTF1, beta-catenin, CDX2, and SSTR2A had a 91% overall accuracy in distinguishing these GI-NEC from P-NEC. This was tested on a second cohort of 10 metastatic GI-NEC and 10 metastatic P-NEC, with an accuracy in this cohort of 85% and an overall accuracy of 89% for the 53 cases tested. Our algorithm reasonably discriminates GI-NEC from P-NEC using currently available IHC stains.

摘要

原发性胃肠道神经内分泌癌(GI-NEC)在形态上无法与肺神经内分泌癌(P-NEC)区分。在原发部位难以确定的情况下,这可能会带来重大的诊断挑战。为了确定可用于可靠区分 GI-NEC 和 P-NEC 的免疫组织化学(IHC)标志物,我们构建了 3 毫米组织微阵列,一个包含 13 个 GI-NEC,另一个包含 20 个 P-NEC。使用 21 种染色剂对两个微阵列进行了 IHC 染色:AE1/AE3、CK7、CK20、突触素、嗜铬粒蛋白、CD56、INSM1、SSTR2A、CDX2、SATB2、TTF1、Napsin A、PR、GATA3、PAX8、ISL1、β-连环蛋白、AFP、SMAD4、Rb 和 p53。对于 GI-NEC,表达最强的标志物是突触素(平均 H 评分 248),而 AE1/AE3 在 P-NEC 中的表达最强(平均 H 评分 230),强于 GI-NEC(p=0.011)。在 P-NEC 中总体表达强于 GI-NEC 的其他标志物包括 CK7(p<0.0001)和 TTF1(p<0.0001)。在 GI-NEC 中总体表达强于 P-NEC 的标志物包括 SSTR2A(p=0.0021)、SATB2(p=0.018)、CDX2(p=0.019)和β-连环蛋白(核;p=0.029)。SMAD4、Rb 和 p53 显示出相似的异常蛋白表达率。基于这些结果,利用 CK7、TTF1、β-连环蛋白、CDX2 和 SSTR2A 的逐步算法方法在区分这些 GI-NEC 和 P-NEC 方面具有 91%的总体准确性。该算法在第二个队列的 10 例转移性 GI-NEC 和 10 例转移性 P-NEC 中进行了测试,在该队列中的准确性为 85%,在测试的 53 例中总体准确性为 89%。我们的算法使用当前可用的 IHC 染色剂合理地区分 GI-NEC 和 P-NEC。

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